Within the area of Reinforcement Learning (RL), it is common
to learn image-to-action mappings, usually in the context of video games
[1]}, [2]}, [3]}, [4]}, [5]}.
By virtue of an existing reward function, the methods learn task-oriented
behavior. Though the imagery may be quite diverse, the underlying task
domain is usually limited in scope relative to the general task of
navigation, and the approaches seek a slightly different purpose
from the one stated here. Though
[6]}, [7]} concern navigation and even
consider specific task-based objectives, the aim of the research
is to demonstrate implicit learning of the environment from imagery based on
repeated trials within the environment. Changing the environment requires
further rounds of training.
